Data Access Layers
Let customers ask plain-English questions of your data.
Your customers should be able to ask questions over your data without learning every layer, filter, dashboard, or reporting workflow first.
Citric Sheep builds data access layers for companies with complex maps, dashboards, portals, and data products, especially where valuable data sits behind layers, filters, and workflows that slow customer self-service.
Book a discovery callWhere we start
Start with one high-value question set.
- Entry point: a paid prototype over one dataset, workflow, or customer problem.
- Success looks like grounded answers tied back to layers, records, maps, reports, or APIs.
- Expansion: production data access layer with evaluation, monitoring, and product integration.
Good fit
For data products customers value but struggle to use.
This is strongest when a company already has valuable data and real users, but customers still depend on support, training, custom reports, or expert interpretation to get useful answers.
- Esri partners and ArcGIS product owners
- Geospatial, environmental, infrastructure, utility, risk, planning, and property data companies
- B2B data platforms with complex dashboards, portals, maps, reports, or analytics products
- Product teams improving customer self-service, onboarding, adoption, or retention
When it matters
Customers need answers without extra help.
The strongest prospects can point to a real gap between having the data and customers being able to use it without help.
Customers need training before they can get value from maps, dashboards, portals, or reports
Support and customer success teams answer the same data-access questions again and again
Users ask for custom reports because the existing interface is hard to interrogate
The product has valuable layers, records, filters, or datasets that non-technical users cannot easily use
What we build
Built as a data access layer.
A data access layer answers from known datasets, APIs, maps, records, and business logic, with traceability and constraints built in from the start.
- A question bank based on real support, sales, onboarding, or product conversations
- A data access map covering layers, records, permissions, APIs, documents, and constraints
- A working data access layer over one high-value dataset or workflow
- Grounded answers with source references, structured outputs, and clear out-of-scope handling
- An evaluation set and production roadmap for expanding the data access layer safely
Choose the first workflow
We pick one valuable dataset, customer problem, or recurring question set so the first engagement is narrow enough to prove.
Map the sources
We review the layers, records, related tables, permissions, documents, APIs, and data-quality constraints that answers need to respect.
Build the answer layer
We create a working interface where users ask questions and receive grounded answers linked back to known sources.
Test and expand
We use an evaluation set to separate what works now, what is out of scope, and what should be added in the production build.
Start with one dataset, one workflow, and one question set.
The usual entry point is a paid prototype over one valuable customer problem, then a production build once the scope is proven.
Book a discovery call